Problem:
ArcGIS Pro has powerful geoprocessing and analysis tools, but many users (especially new analysts, planners, and field teams) struggle to know which tools to chain together, how to set parameters correctly, and how to validate results. Current AI assistants provide guidance or Arcade snippets, but they don’t act on behalf of the user. This leads to long learning curves, errors, and lost productivity.
Enhancement:
Introduce an Agentic AI Assistant in ArcGIS Pro that can:
Understand intent – Parse natural language requests like “Find flood-prone areas within 1 mile of hospitals and rank them by population density.”
Plan workflows – Identify the sequence of geoprocessing tools (e.g., Select Layer by Location → Buffer → Intersect → Summarize Within).
Execute actions – Build and run workflows in ModelBuilder or ArcPy automatically.
Validate outputs – Check for projection mismatches, missing data, or empty outputs and suggest corrections.
Document results – Save workflows as ModelBuilder diagrams or Python scripts, and generate plain-language explanations of what was done and why.
Use Cases:
Urban planning: An analyst can ask “Map areas most vulnerable to extreme heat by combining land cover, population density, and proximity to cooling centers.” The Agentic AI plans and executes the workflow, produces a vulnerability map, and saves the script for reuse.
Emergency management: During a wildfire event, staff can request “Identify communities within 5 miles of active fire perimeters with elderly population density above threshold.” AI retrieves data layers, buffers perimeters, intersects census data, and returns both maps and reports.
Learning & productivity: New GIS staff can learn faster by watching how the AI builds workflows and reviewing the auto-generated ModelBuilder diagram or ArcPy code.
Value:
Accessibility: Non-technical staff can use advanced GIS tools without deep training.
Speed: Analysts save time on repetitive setup and troubleshooting.
Quality: Automated validation reduces human error in geoprocessing.
Transparency: Documented workflows improve reproducibility and trust.
